Shashank Gandhi HHS Public Access Maximilian Haeussler ... · CRISPR/Cas9 system to induce...

Evaluation and rational design of guide RNAs for efficient CRISPR/Cas9-mediated mutagenesis in Ciona

Shashank Gandhia,1, Maximilian Haeusslerb, Florian Razy-Krajkaa, Lionel Christiaena,*, and Alberto Stolfia,*

aDepartment of Biology, New York University, New York, USA

bSanta Cruz Genomics Institute, MS CBSE, University of California, Santa Cruz, USA

Abstract

The CRISPR/Cas9 system has emerged as an important tool for various genome engineering

applications. A current obstacle to high throughput applications of CRISPR/Cas9 is the imprecise

prediction of highly active single guide RNAs (sgRNAs). We previously implemented the

CRISPR/Cas9 system to induce tissue-specific mutations in the tunicate Ciona. In the present

study, we designed and tested 83 single guide RNA (sgRNA) vectors targeting 23 genes expressed

in the cardiopharyngeal progenitors and surrounding tissues of Ciona embryo. Using high-

throughput sequencing of mutagenized alleles, we identified guide sequences that correlate with

sgRNA mutagenesis activity and used this information for the rational design of all possible

sgRNAs targeting the Ciona transcriptome. We also describe a one-step cloning-free protocol for

the assembly of sgRNA expression cassettes. These cassettes can be directly electroporated as

unpurified PCR products into Ciona embryos for sgRNA expression in vivo, resulting in high

frequency of CRISPR/Cas9-mediated mutagenesis in somatic cells of electroporated embryos. We

found a strong correlation between the frequency of an Ebf loss-of-function phenotype and the

mutagenesis efficacies of individual Ebf-targeting sgRNAs tested using this method. We anticipate

that our approach can be scaled up to systematically design and deliver highly efficient sgRNAs

for the tissue-specific investigation of gene functions in Ciona.

Keywords

sgRNA; cardiopharyngeal mesoderm; tunicate

Introduction

A platform for targeted mutagenesis has been recently developed based on the prokaryotic

immune response system known as CRISPR/Cas (Clustered Regularly Interspaced Short

Palindromic Repeats/CRISPR-Associated) (Barrangou et al. 2007). In its most common

*Corresponding authors: [email protected] (L.C.), [email protected] (A.S.).1Current address: Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA

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HHS Public AccessAuthor manuscriptDev Biol. Author manuscript; available in PMC 2018 May 01.

Published in final edited form as:Dev Biol. 2017 May 01; 425(1): 8–20. doi:10.1016/j.ydbio.2017.03.003.

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derivation for genome engineering applications, the system makes use of a short RNA

sequence, known as a single guide RNA (sgRNA) to direct the Cas9 nuclease of

Streptococcus pyogenes to a specific target DNA sequence. (Jinek et al. 2012; Cong et al. 2013; Jinek et al. 2013; Mali et al. 2013). Although initial Cas9 binding requires a

Protospacer Adjacent Motif (PAM) sequence, most commonly “NGG”, the high specificity

of this system is accounted for by Watson-Crick base pairing between the 5′ end of the

sgRNA and a 17–20bp “protospacer” sequence immediately adjacent to the PAM (Fu et al. 2014). Upon sgRNA-guided binding to the intended target, Cas9 generates a double stranded

break (DSB) within the protospacer sequence. Imperfect repair of these DSBs by non-

homologous end joining (NHEJ) often results in short insertions or deletions (indels) that

may disrupt the function of the targeted sequence. Numerous reports have confirmed the

high efficiency of CRISPR/Cas9 for genome editing purposes (Dickinson et al. 2013;

Hwang et al. 2013; Wang et al. 2013a; Koike-Yusa et al. 2014; Paix et al. 2014; Shalem et al. 2014; Wang et al. 2014; Gantz and Bier 2015; Sanjana et al. 2016).

The tunicate Ciona is a model organism for the study of chordate-specific developmental

processes (Satoh 2013). The CRISPR/Cas9 system was adapted to induce site-specific DSBs

in the Ciona genome (Sasaki et al. 2014; Stolfi et al. 2014). Using electroporation to

transiently transfect Ciona embryos with plasmids encoding CRISPR/Cas9 components, we

were able to generate clonal populations of somatic cells carrying loss-of-function mutations

of Ebf, a transcription-factor-coding gene required for muscle and neuron development, in

F0-generation embryos (Stolfi et al. 2014). By using developmentally regulated cis-

regulatory elements to drive Cas9 expression in specific cell lineages or tissue types, we

were thus able to control the disruption of Ebf function with spatiotemporal precision.

Following this proof-of-principle, tissue-specific CRISPR/Cas9 has rapidly propagated as a

simple yet powerful tool to elucidate gene function in the Ciona embryo (Abdul-Wajid et al. 2015; Cota and Davidson 2015; Segade et al. 2016; Tolkin and Christiaen 2016).

We sought to expand the strategy to target more genes, with the ultimate goal of building a

genome-wide library of sgRNAs for systematic genetic loss-of-function assays in Ciona embryos. However, not all sgRNAs drive robust CRISPR/Cas9-induced mutagenesis, and

few guidelines exist for the rational design of highly active sgRNAs, which are critical for

rapid gene disruption in F0. This variability and unpredictable efficacy demands

experimental validation of each sgRNA tested. Individual studies have revealed certain

nucleotide sequence features that correlate with high sgRNA expression and/or activity in

CRISPR/Cas9-mediated DNA cleavage (Doench et al. 2014; Gagnon et al. 2014; Ren et al. 2014; Wang et al. 2014; Chari et al. 2015; Fusi et al. 2015; Housden et al. 2015; Moreno-

Mateos et al. 2015; Wong et al. 2015; Xu et al. 2015; Doench et al. 2016). These studies

have been performed in different organisms using a variety of sgRNA and Cas9 delivery

methods and show varying ability to predict sgRNA activities across platforms (Haeussler et al. 2016).

Given the uncertainty regarding how sgRNA design principles gleaned from experiments in

other species might be applicable to Ciona, we tested a collection of sgRNAs using our own

modified tools for tissue-specific CRISPR/Cas9-mediated mutagenesis in Ciona embryos.

We describe here the construction and validation of this collection using high-throughput

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sequencing of PCR-amplified target sequences. This dataset allowed us to develop a

practical pipeline for optimal design and efficient assembly of sgRNA expression constructs

for use in Ciona.

Results

High-Throughput sequencing to estimate sgRNA-specific mutagenesis rates

Previous studies using CRIsPR/Cas9-based mutagenesis in Ciona revealed that different

sgRNAs have varying ability to induce mutations (Sasaki et al. 2014; Stolfi et al. 2014). In

order to test a larger number of sgRNAs and identify parameters that may influence

mutagenesis efficacy, we constructed a library of 83 sgRNA expression plasmids targeting a

set of 23 genes (Table 1). The majority of these genes are transcription factors and signaling

molecules of potential interest in the study of cardiopharyngeal mesoderm development. The

cardiopharyngeal mesoderm of Ciona, also known as the Trunk Ventral Cells (TVCs), are

multipotent cells that invariantly give rise to the heart and pharyngeal muscles of the adult

(Hirano and Nishida 1997; Stolfi et al. 2010; Razy-Krajka et al. 2014), thus sharing a

common ontogenetic motif with the cardiopharyngeal mesoderm of vertebrates (Wang et al. 2013b; Diogo et al. 2015; Kaplan et al. 2015).

We followed a high-throughput-sequencing-based approach to quantify the efficacy of each

sgRNA, i.e. its ability to cause CRISPR/Cas9-induced mutations in targeted sequences in the

genome (Figure 1a–c). The 83 sgRNA plasmids were co-electroporated with

Eef1a1>nls∷Cas9∷nls plasmid. The ubiquitous Eef1a1 promoter is active in all cell lineages

of the embryo and has been used to express a variety of site-specific nucleases for targeted

somatic knockouts in Ciona (Sasakura et al. 2010; Kawai et al. 2012; Sasaki et al. 2014;

Stolfi et al. 2014; Treen et al. 2014). Each individual sgRNA + Cas9 vector combination was

electroporated into pooled Ciona zygotes, which were then grown at 18°C for 16 hours post-

fertilization (hpf; embryonic stage 25)(Hotta et al. 2007). Targeted sequences were

individually PCR-amplified from each pool of embryos. Each target was also amplified from

“negative control” embryos grown in parallel and electroporated with Eef1a1>nls∷Cas9∷nls and “U6>Negative Control” sgRNA vector. Agarose gel-selected and purified amplicons

(varying from 108 to 350 bp in length) were pooled in a series of barcoded “targeted” and

“negative control” Illumina sequencing libraries and sequenced using the Illumina MiSeq

platform.

Alignment of the resulting reads to the reference genome sequence (Satou et al. 2008)

revealed that targeted sites were represented on average by 16,204 reads, with a median of

3,899 reads each (Supplementary Table 1). The ability of each sgRNA to guide Cas9 to

induce DSBs at its intended target was detected by the presence of insertions and deletions

(indels) within the targeted protospacer + PAM. The ratio of [indels]/[total reads] represents

our estimation of the mutagenesis efficacy of the sgRNA (Figure 1b–d, Supplementary Table

1). For each mutation, an unknown number of cell divisions occur between the moment

Cas9 induces a DSB and the time of sample collection and genomic DNA extraction. This

prevents us from quantifying the true mutagenesis rates. However, we can surmise that this

applies comparably to all sgRNAs, such that our values still represent an accurate ranking of

mutagenesis efficacy.

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For simplicity, we did not count single nucleotide point mutations, even though a fraction of

them may result from NHEJ-repair of a DSB event. Our data indicated that all sgRNAs (with

the exception of Neurog.2) were able to induce DSBs, with estimated efficacies varying

from 0.05% (Ebf.4) to 59.63% (Htr7-r.2). Although each sgRNA was tested only once, we

did not observe any evidence of electroporation variability or batch effects that may have

confounded our estimates (Supplementary Figure 1).

This conservative approach most likely underestimates the actual mutagenesis rates. First,

we excluded point mutations potentially resulting from imperfect DSB repair. Second, but

more importantly, amplicons from transfected cells are always diluted by wild-type

sequences from untransfected cells in the same sample, due to mosaic incorporation of

sgRNA and Cas9 plasmids. Indeed, we previously observed an enrichment of mutated

sequences amplified from reporter transgene-expressing cells isolated by magnetic-activated

cell sorting (representing the transfected population of cells) relative to unsorted cells

(representing mixed transfected and untransfected cells) (Stolfi et al. 2014). In that particular

example, the estimated mutagenesis efficacy induced by the Ebf.3 sgRNA was 66% in sorted

sample versus 45% in mixed sample. This suggests the actual efficacies of some sgRNAs

may be up to 1.5-fold higher than their estimated rates.

Analysis of unique indels generated by the activity of two efficient sgRNAs, Ebf.3 and

Lef1.2, indicated a bias towards deletions rather than insertions, at a ratio of roughly 2:1

deletions:insertions (Figure 1e). However, these two sgRNAs generated different

distributions of indel lengths, indicating indel position and size may depend on locus-

specific repair dynamics as previously shown (Bae et al. 2014).

Numerous studies have reported the potential off-target effects of CRISPR/Cas9 in different

model systems (Fu et al. 2013; Hsu et al. 2013; Pattanayak et al. 2013; Cho et al. 2014). For

this study, we were able to mostly select highly specific sgRNAs, owing to the low

frequency of predicted off-target sequences in the small, A/T-rich Ciona genome (see

Discussion for details). To test the assumption that off-target DSBs are unlikely at partial

sgRNA seed-sequence matches, we analyzed the mutagenesis rates at two potential off-

target sites that matched the protospacer at the 10 and 8 most PAM-proximal positions of the

Ebf.3 and Fgf4/6.1 sgRNAs, respectively. We did not detect any mutations in 5,570 and

6,690 reads mapped to the two loci, respectively, suggesting high specificity of the

sgRNA:Cas9 complex to induce DSBs only at sites of more extensive sequence match.

Identifying sequence features correlated with sgRNA efficacy

We analyzed our dataset for potential correlations between target sequence composition and

sgRNA-specific mutagenesis rate (excluding the Bmp2/4.1 sgRNA because only two reads

mapped to its target sequence). We hypothesized that, if mutagenesis efficacy can be

predicted by nucleotide composition at defined positions in the protospacer and flanking

sequences, then comparing the target sequences of the most or least active sgRNAs in our

dataset should reveal features that affect CRISPR/Cas9 efficacy in Ciona. To that effect, we

performed nucleotide enrichment analyses for the top and bottom 25% sgRNAs ranked by

measured mutagenesis efficacy (Figure 2)(Schneider and Stephens 1990; Crooks et al. 2004). For the top 25% sgRNAs, guanine was overrepresented in the PAM-proximal region,

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while the ambiguous nucleotide of the PAM (‘N’ in ‘NGG’) was enriched for cytosine. We

also observed an overall depletion of thymine in the protospacer sequence for the top 25%

sgRNAs, likely due to premature termination of PolIII-driven transcription as previously

demonstrated (Wu et al. 2014). Among the bottom 25% sgRNAs, we observed a higher

representation of cytosine at nucleotide 20 of the protospacer (Figure 2). All these

observations are consistent with the inferences drawn from previous studies, suggesting that

certain sgRNA and target sequence features that influence Cas9:sgRNA-mediated

mutagenesis rates are consistent across different experimental systems (Gagnon et al. 2014;

Ren et al. 2014; Wu et al. 2014; Chari et al. 2015; Moreno-Mateos et al. 2015; Haeussler et al. 2016).

Several studies in different model organisms have similarly examined the nucleotide

preferences amongst sgRNAs inducing high or low rates of mutagenesis, and put forth

predictive heuristics and/or algorithms for the rational design of highly active sgRNAs

(Doench et al. 2014; Gagnon et al. 2014; REN et al. 2014; WANG et al. 2014; CHARI et al. 2015; FUSI et al. 2015; HOUSDEN et al. 2015; Moreno-Mateos et al. 2015; Wong et al. 2015; Xu et al. 2015; Doench et al. 2016). These various algorithms have been evaluated,

summarized, and aggregated by the CRISPR sgRNA design web-based platform CRISPOR

(Haeussler et al. 2016). According to this metaanalysis, the “Fusi/Doench” algorithm (“Rule

Set 2”)(FUSI et al. 2015; DOENCH et al. 2016) is the best at predicting the activities of

sgRNA transcribed in vivo from a U6 small RNA promoter transcribed by RNA Polymerase

III (PolIII), while CRISPRscan is recommended for sgRNAs transcribed in vitro from a T7

promoter (Moreno-Mateos et al. 2015).

Ciona rearing conditions differ from most other model systems, being a marine invertebrate

that develops optimally at 16–24°C (Bellas et al. 2003). Moreover, most CRISPR/Cas9-

based experiments in Ciona rely on in vivo transcription of sgRNAs built with a modified “F

+E” backbone (Chen et al. 2013) by a Ciona-specific U6 promoter (Nishiyama and Fujiwara

2008). We used CRISPOR to calculate predictive scores for all sgRNAs in our data set and

compare these scores to our mutagenesis efficacy measurements for each (Figure 3a,

Supplementary Table 1). We found that indeed the Fusi/Doench score best correlated with

our measured sgRNA efficacies, with a Spearman’s rank correlation coefficient (rho) of

0.435 (p=3.884e-05)(Figure 3a). CRISPRscan, the algorithm based on in vitro-, T7-

transcribed sgRNAs injected into zebrafish, was less predictive (rho = 0.344, p=0.001435)

(Supplementary Table 1), supporting the conclusion that sgRNA expression method (e.g. U6

vs. T7) accounts for an important parameter when choosing an sgRNA design algorithm.

Scores computed by other published algorithms available on the CRISPOR platform did not

yield good correlations with our measurements (Supplementary Table 1), indicating these

are perhaps not suited for predicting sgRNA activity in Ciona.

In a previous study, highly penetrant, tissue-specific loss-of-function phenotypes in F0

embryos were elicited using the Ebf.3 sgRNA (Stolfi et al. 2014), which in our current study

had a measured mutagenesis efficacy of 37%. Further comparison of measured mutagenesis

efficacy and mutant phenotype frequency for a series of Ebf-targeting sgRNAs revealed that

an estimated sgRNA efficacy at least 25% correlated with over 70% reduction in the

frequency of embryos expressing an Islet reporter construct (see below and Figure 6). We

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thus reasoned that a mutagenesis efficacy of ~25% would be the minimum threshold of

acceptable sgRNA activity for loss-of-function assays in F0. Within our dataset, among the

sgRNAs that had a Fusi/Doench score >60, 18 of 23 (78%) had a mutagenesis efficacy rate

over 24% (Figure 3b). In contrast, only 8 of 25 (32%) of sgRNAs with a Fusi/Doench score

<50 had an efficacy over 24% (Figure 3b). Indeed, a receiver operating characteristic (RoC)

analysis showed an area under the curve (AUC) of 0.77 when using Fusi/Doench score as a

classifier of “good” (>24.5% efficacy) vs. “bad” (≤24.5%) sgRNAs (Figure 3c). The most

accurate Fusi/Doench score cutoffs appeared to be between 50 and 55, when taking both

specificity and sensitivity into account (Supplementary Table 2, Supplementary Figure 2).

However, if the number of candidate sgRNAs is not limiting, it may be more desirable to use

a Fusi/Doench score cutoff of 60 in order to avoid false positives (i.e., sgRNAs that are

predicted as “good” when in reality they are “bad”). Thus, for Ciona, we recommend using

CRISPOR to select sgRNAs with Fusi/Doench scores >60 and avoid those with Fusi/Doench

<50. We believe this approach will significantly streamline the search for suitable U6

promoter-driven sgRNAs targeting one’s gene of interest.

Multiplexed targeting with CRISPR/Cas9 generates large deletions in the Ciona genome

Large deletions of up to 23 kb of intervening DNA resulting from NHEJ between two

CRISPR/Cas9-induced DSBs have been reported in Ciona (Abdul-Wajid et al. 2015). For

functional analyses of protein-coding genes, such deletions would more likely produce null

mutations than small deletions resulting from the action of lone sgRNAs. To test whether we

could cause tissue-specific large deletions in F0 embryos, we targeted the forkhead/winged

helix transcription-factor-encoding gene Foxf (Figure 4a), which contributes to

cardiopharyngeal development in Ciona (Beh et al. 2007). We co-electroporated

Eef1a1>nls∷Cas9∷nls with sgRNA vectors Foxf.4 and Foxf.2 (with induced mutagenesis

rates of 39% and 18%, respectively). We extracted genomic DNA from electroporated

embryos and PCR-amplified the sequence spanning both target sites. We obtained a specific

~300 bp PCR product corresponding to the amplified region missing the ~2.1 kbp of

intervening sequence between the two target sites (Figure 4b). Cloning the deletion band and

sequencing individual clones confirmed that the short PCR product corresponds to a deletion

of most of the Foxf first exon and 5′ cis-regulatory sequences (Beh et al. 2007). We did not

detect this deletion using genomic DNA extracted from embryos electroporated with either

sgRNA alone. Similar deletion PCR products were observed, cloned, and sequenced for

other genes including Nk4, Fgfr, Mrf, Htr7-related, Bmp2/4, and Hand, using pairs of highly

mutagenic sgRNAs (Supplementary Figure 3). The largest deletion recorded was ~3.6 kbp,

with sgRNAs Nk4.2 (46% efficacy) and Nk4.3 (38% efficacy), entirely removing the sole

intron of Nk4 and small portions of the flanking exons. The sgRNAs targeting Mrf were

shown to inhibit its function and subsequent siphon muscle development (Tolkin and

Christiaen 2016).

Foxf is expressed in TVCs and head epidermis (Figure 4c), the latter of which is derived

exclusively from the animal pole (Nishida 1987; Imai et al. 2004; Pasini et al. 2006; Beh et al. 2007). Because the ~2.1 kbp deletion introduced in the Foxf locus excised the epidermal

enhancer and basal promoter (Beh et al. 2007), we sought to examine the effects of these

large deletions on Foxf transcription. We used the cis-regulatory sequences from Zfpm (also

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known as Friend of GATA, or Fog, and referred to as such from here onwards) to drive Cas9

expression in early animal pole blastomeres (Rothbächer et al. 2007). We electroporated

Fog>nls∷Cas9∷nls together with Foxf.2 and Foxf.4 sgRNA vectors and Fog>H2B∷mCherry,

and raised embryos at 18°C for 9.5 hpf (early tailbud, embryonic stage 20). We performed

whole mount mRNA in situ hybridization to monitor Foxf expression, expecting it to be

silenced in some epidermal cells by tissue-specific CRISPR/Cas9-induced deletions of the

Foxf cis-regulatory sequences on both homologous chromosomes in each cell. Indeed, we

observed patches of transfected head epidermal cells (marked by H2B∷mCherry) in which

Foxf expression was reduced or eliminated (Figure 4d). This was in contrast to the uniform,

high levels of Foxf expression observed in “control” embryos electroporated with Ebf.3

sgRNA (Ebf is unlikely to be involved in Foxf regulation in the epidermis where it is not

expressed, Figure 4c). Taken together, these results indicate that, by co-electroporating two

or more highly active sgRNAs targeting neighboring sequences, one can frequently generate

large deletions in the Ciona genome in a tissue-specific manner.

Rapid generation of sgRNA expression cassettes ready for embryo transfection

CRISPR/Cas9 is an efficient and attractive system for targeted mutagenesis in Ciona, but

cloning individual sgRNA vectors is a labor-intensive, rate-limiting step. To further expedite

CRISPR/Cas9 experiments, we adapted a one-step overlap PCR (OSO-PCR) protocol to

generate U6 promoter>sgRNA expression “cassettes” for direct electroporation without

purification (Figure 5, Supplementary Figure 4, see Materials and Methods and

Supplementary Protocol for details). We tested the efficacy of sgRNAs expressed from these

unpurified PCR products, by generating such expression cassettes for the validated Ebf.3

sgRNA. We electroporated Eef1a1>nls∷Cas9∷nls and 25 μl (corresponding to ~2.5 μg, see

Materials and Methods and Supplementary Figure 5) of unpurified, U6>Ebf.3 sgRNA

OSO-PCR or U6>Ebf.3 sgRNA traditional PCR products (total electroporation volume: 700

μl). Next-generation sequencing of the targeted Ebf.3 site revealed mutagenesis rates similar

to those obtained with 75 μg of U6>Ebf.3 sgRNA plasmid (Supplementary Table 1). This

was surprising given the much lower total amount of DNA electroporated from the PCR

reaction relative to the plasmid prep (2.5 μg vs. 75 μg). This discrepancy could indicate a

higher efficiency of transcription of linear vs. circular transfected DNA, though more

thorough analyses are warranted to investigate the behavior of linear DNA in Ciona embryos.

To assess whether unpurified sgRNA PCR cassettes could be used in CRISPR/Cas9-

mediated loss-of-function experiments in F0 embryos, we assayed the expression of an Islet reporter transgene in MN2 motor neurons (RYAN et al. 2016), which depends upon Ebf

function (STOLFI et al. 2014). Indeed, Islet>GFP expression was downregulated in embryos

electroporated with Sox1/2/3>nls∷Cas9∷nls and 25 μl of unpurified U6>Ebf.3 traditional

PCR or 25μg U6>Ebf.3 plasmid, but not with 25 μl (~2.5 μg) of unpurified U6>Negative Control sgRNA PCR cassette (Figure 6a–d). Taken together, these results indicate that

unpurified PCR products can be used in lieu of plasmids to express sgRNAs for tissue-

specific CRISPR/Cas9-mediated mutagenesis in Ciona embryos.

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Correlation between sgRNA efficacy and mutant phenotype penetrance

Since we measured a wide range of mutagenesis efficacies across our library of 83 sgRNAs,

we wanted to assess how this variability correlates with mutant phenotype penetrance. One

possibility is that sgRNA efficacies and frequencies of mutant phenotypes in F0 are linearly

correlated. Alternatively, mutant phenotypes might only be observed at distinct thresholds of

sgRNA activity.

To test this, we designed 7 additional sgRNAs (Ebf.A through Ebf.G) targeting the IPT and

HLH domain-coding exons of Ebf (Figure 6a,e, Supplementary Table 3). We generated these

sgRNA expression cassettes by OSO-PCR, and co-electroporated 25 μl of each reaction with

either 25 μg Eef1a1>nls∷Cas9∷nls (for mutagenesis efficacy sequencing) or 40 μg

Sox1/2/3>nls∷Cas9∷nls + 15 μg Sox1/2/3>H2B∷eGFP + 40 μg Islet>mCherry (for

phenotype assay). sgRNA efficacies were measured by direct Sanger sequencing of the

target region PCR-amplified from larvae electroporated with the former combination (see

Materials and methods for details), and Islet>mCherry expression in H2B∷eGFP+ motor

neurons was scored in larvae electroporated with the latter mix.

Quantification of indel-shifted electrophoresis chromatogram peaks (“Peakshift” assay)

revealed sgRNA mutagenesis efficacies ranging from 5% to 43% (Figure 6e, Supplementary

Table 3). Of note, the sgRNA with the lowest efficacy (Ebf.E) was clearly hampered by a

naturally occurring SNP that eliminates the PAM (NGG to NGA) in a majority of

haplotypes. In parallel, the proportion of transfected embryos Islet>mCherry expression was

observed to vary between 0% and 94%. When this was plotted against the measured

mutagenesis efficacies, we observed a nearly perfect linear correlation between the mutant

phenotype (loss of Islet>mCherry expression) and Ebf mutagenesis (Figure 6e,

Supplementary Table 3). Taken together, these results suggest that highly efficient sgRNAs

can be generated from OSO-PCR cassettes and validated for loss-of-function studies by

Sanger sequencing. The Sanger sequencing-based peakshift assay is highly reproducible and

approximates the efficacy rates estimated by NGS (Supplementary Table 6). As such, we

recommend the peakshift assay as a cheap, fast alternative for testing sgRNA activity in

Ciona embryos.

Genome-wide design and scoring of sgRNAs for Ciona

While Ciona researchers will find the Fusi/Doench scoring system and the OSO-PCR

method useful for sgRNA expression cassette design and assembly, we hoped to further

empower the community by pre-emptively designing all possible sgRNAs with a unique

target site within 200 bp of all Ciona exonic sequences. We computationally identified

3,596,551 such sgRNAs. We have compiled all sgRNA sequences and their corresponding

specificity and efficiency scores (including Fusi/Doench). They are available as a UCSC

Genome Browser track for the Ci2 genome assembly (http://genome.ucsc.edu/)[FOR PEER

REVIEW ONLY: http://genome-test.soe.ucsc.edu], with links to CRISPOR for off-target

prediction and automated OSO-PCR primer design. This track is freely available for

download to use on other browsers, like those of specific interest to the tunicate community

such as ANISEED (Brozovic et al. 2015) or GHOST (Satou et al. 2005).

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http://genome.ucsc.edu/

http://genome-test.soe.ucsc.edu

Discussion

We have built a library of 83 plasmid vectors for the in vivo expression of sgRNAs targeting

23 genes expressed in the cardiopharyngeal mesoderm and surrounding tissues, mostly

hypothesized to be involved in regulating the specification of heart and/or pharyngeal

muscles in Ciona, even though many have complex expression patterns and probably

pleiotropic functions. We have also established reliable protocols for the validation of

sgRNA efficacy in electroporated Ciona embryos by either next-generation sequencing or

Sanger sequencing. This has allowed us to estimate the activity of all these sgRNAs, which

are ready to be used for ongoing and future functional studies.

By analyzing correlations between target sequence nucleotide composition and sgRNA

mutagenesis efficacy, we identified sgRNA sequence features that may contribute to

Cas9:sgRNA activity. Some of these sequence features have been identified in previous

CRISPR/Cas9-mediated mutagenesis screens performed in other metazoan model

organisms, suggesting that these are determined by the intrinsic properties of sgRNAs and/or

Cas9 (Doench et al. 2014; Gagnon et al. 2014; Ren et al. 2014; Chari et al. 2015; Moreno-

Mateos et al. 2015). For instance, sgRNA efficacy is correlated with increased guanine

content in the PAM-proximal nucleotides of the sgRNA, postulated to be due to increased

sgRNA stability by G-quadruplex formation (Moreno-Mateos et al. 2015). This would

explain the specific enrichment for guanine but not cytosine, even if both could in theory

augment sgRNA folding or binding to target DNA. We also encountered a depletion of

thymine and cytosine in the PAM-proximal nucleotides of the protospacers for highly active

sgRNAs. The strong negative correlation between sgRNA efficacy and thymine content of

the protospacer is easily attributed to our use of the PolIII-dependent U6 promoter to express

our sgRNAs. It has been shown that termination of transcription by PolIII can be promoted

by degenerate poly-dT tracts (NIELSEN et al. 2013). A high number of non-consecutive

thymines clustered in the protospacer could thus result in lower sgRNA expression level due

to premature termination of sgRNA transcription (STOLFI et al. 2014; Wu et al. 2014).

Similarly, adenines are thought to contribute to the instability of sgRNAs (Moreno-Mateos et al. 2015), suggesting that CRISPR/Cas9 mutagenesis efficacies might be primarily

determined by sgRNA transcription and degradation rates, which will vary depending on the

species studied and the mode of sgRNA delivery (e.g. in vitro vs. in vivo synthesis).

Despite the lack of biological replicates for the NGS-based measurements, we have

presented different data suggesting that sgRNA mutagenesis efficacies are reproducible

between experiments, and not greatly affected by electroporation variability. First and

foremost, we found a high correlation (Spearman’s rank correlation coefficient of 0.435,

p=3.884e-05) between our NGS data and scores from the predictive Fusi/Doench algorithm

(Figure 3). One would expect little correlation between our NGS data and predicted scores

(by any algorithm) if the variation observed in our data were caused by technical variability

and not innate sgRNA efficacy. Second, all three Ebf.3 sgRNA vector formats (plasmid,

traditional PCR cassette, OSO-PCR cassette) resulted in very similar mutagenesis efficacies

by NGS (30.2%–37.3%), Supplementary Table 1). Third, there was a high correlation

between mutagenesis efficacies of Ebf-targeting sgRNAs and Ebf loss-of-function

phenotypes, which were assayed in two separate sets of experiments (Figure 6e). Lastly,

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there was little variability in efficacy between biological replicates of a subset of sgRNAs as

measured by peakshift (Supplementary Table 6).

Although more replicates and better statistical support would be required to develop a

Ciona-specific sgRNA prediction algorithm de novo, we believe our data are accurate

enough to support using the Fusi/Doench algorithm as the gold-standard in sgRNA design

for Ciona (Figure 3). Among the various published sgRNA prediction algorithms, Fusi/

Doench (FUSI et al. 2015; DOENCH et al. 2016) functions well as a classifier for “good”

(>24.5% mutagenesis efficacy) and “bad” (<24.5%) sgRNAs. Despite these general trends,

several sgRNAs defied this algorithm-based prediction. This suggests that there are multiple,

possibly additive or synergistic factors that determine the mutagenesis efficacy, only one of

which is primary sequence composition of the sgRNA or target. Other factors that can

influence Cas9 binding include chromatin accessibility and nucleosome occupancy (Wu et al. 2014; HINZ et al. 2015; HORLBECK et al. 2016; ISAAC et al. 2016). What other

additional factors contribute to variability of in vivo sgRNA mutagenesis efficacies will be

an important topic of study as CRISPR/Cas9-based approaches are expanded to address

additional questions in basic research as well as for therapeutic purposes.

While an optimized predictive algorithm for Ciona-specific sgRNA design remains a

desirable goal, our current approach should help other researchers to identify, with greater

confidence, which sgRNAs are likely to confer enough mutagenic activity for functional

studies in F0. We have shown, using a series of Ebf-targeting sgRNAs and an Ebf loss-of-

function readout assay (Islet reporter expression) that a linear correlation exists between

sgRNA mutagenesis efficacy and the probability of somatic gene knockout in F0. In this

case, we measured the frequency of a binary loss-of-function assay (Islet ON or OFF) in a

large population of embryos. Therefore it is expected that the probability a homozygous Ebf knockout (resulting in Islet OFF phenotype) should be correlated to the observed frequency

of Ebf mutations in somatic cell populations. While Ebf function can be disrupted by small

changes to its crucial IPT/HLH domains, other genes may prove harder to disrupt with the

short indels generated by CRISPR/Cas9. However, we show that the combinatorial action of

two or more sgRNAs can result in high frequency of large deletions spanning many kbp,

which should help generate loss-of-function alleles for such recalcitrant genes.

Despite legitimate concerns about potential off-target effects for functional studies, we were

not able to detect CRISPR/Cas9-mediated mutagenesis at two potential off-target sites for

the sgRNAs Ebf.3 and Fgf4/6.1. For the remainder of the sgRNAs, we purposefully selected

those with no strongly predicted off-targets. This was possible in Ciona due to two factors.

First, the Ciona genome is significantly smaller than the human genome and most

metazoans, resulting in a lower number of similar protospacer sequences. Second, the GC

content of the Ciona genome is only 35% as compared to 65% in humans, which should

result in a lower overall frequency of canonical PAMs (NGG). Based on these

considerations, we predict off-target effects to be less pervasive in Ciona than in other model

organisms with more complex, GC-rich genomes.

Even with improved prediction of sgRNA efficacy and specificity, there is still a need to test

several sgRNAs to identify the optimal one targeting a gene of interest. To this end, we have

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developed a cloning-free OSO-PCR method for the rapid assembly of sgRNA expression

cassettes. We have shown that these unpurified PCR cassettes can be directly electroporated

into Ciona embryos and screened by either Sanger sequencing of target sequences or mutant

phenotype frequency in F0. The automated design of primers for Ciona-specific sgRNA

cassette OSO-PCR has been implemented in the latest version (v4.0) of CRISPOR (http://

crispor.tefor.net/).

Finally, we have pre-emptively designed all possible sgRNAs targeting exonic sequences in

the compact Ciona genome and calculated their specificity and efficiency by various

predictive algorithms. This track is available online on the UCSC genome browser, but is

also freely available for download and use with other genome browsers. This allows

researchers to locally browse for sgRNAs with predicted high activity targeting their loci of

interest. Integration with the CRISPOR website further allows SNP and off-target prediction,

and pre-designed OSO-PCR oligonucleotide primers for rapid, efficient synthesis and

transfection. We expect these resources to facilitate the scaling of CRISPR/Cas9-mediated

targeted mutagenesis and enable genome-wide screens for gene function in Ciona.

Materials and Methods

Target sequence selection and sgRNA design

23 genes from Ciona robusta (formerly Ciona intestinalis type A)(HOSHINO AND

TOKIOKA 1967; BRUNETTI et al. 2015) hypothesized to be important for

cardiopharyngeal mesoderm development were shortlisted (Table 1) and one to four sgRNAs

targeting non-overlapping sequences per gene were designed, for a total of 83 sgRNA

vectors (Supplementary Table 3). Two sgRNAs were designed to target the neurogenic

bHLH factor Neurogenin, a gene that is not expressed in the cardiopharyngeal mesoderm

and is not thought to be involved in cardiopharyngeal development. Target sequences were

selected by searching for N19+NGG (protospacer + PAM) motifs and screened for

polymorphisms and off-target matches using the GHOST genome browser and BLAST

portal (Satou et al. 2005; Satou et al. 2008). Potential off-targets were also identified using

the CRISPRdirect platform (Naito et al. 2015). sgRNA expression plasmids were designed

for each of these protospacers and constructed using the U6>sgRNA(F+E) vector as

previously described (Stolfi et al. 2014), as well as a “Negative Control” protospacer that

does not match any sequence in the C. robusta genome (5′-

GCTTTGCTACGATCTACATT-3′). Stretches of more than four thymine bases (T) were

avoided due to potential premature transcription termination. Candidate sgRNAs with a

partial PAM-proximal match of 13 bp or more to multiple loci were also discarded due to

off-target concerns. All sgRNAs were designed to target protein-coding, splice-donor, or

splice-acceptor sites, unless specifically noted. We preferred more 5′ target sites, as this

provides a greater probability of generating loss-of-function alleles.

Electroporation of Ciona embryos

DNA electroporation was performed on pooled, dechorionated zygotes (1-cell stage

embryos) from C. robusta adults collected from San Diego, CA (M-REP) as previously

described (Christiaen et al. 2009). All sgRNA plasmid maxipreps were individually

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electroporated at a final concentration of 107 ng/μl (75 μg in 700 μl) concentration together

with Eef1a1>nls∷Cas9∷nls plasmid (Stolfi et al. 2014) at 35.7 ng/μl (25 μg in 700 μl)

concentration. For testing U6>Ebf.3 PCR or OSO-PCR, 25 μl was used instead of sgRNA

plasmid. Embryos were then rinsed once in artificial sea water, to remove excess DNA and

electroporation buffer, and grown at 18°C for 16 hours post-fertilization.

Embryo lysis

After 16 hpf, each pool of embryos targeted with a single sgRNA + Cas9 combination was

washed in one sea water exchange before lysis, to remove excess plasmid DNA, and

transferred to a 1.7 ml microcentrifuge tube. Excess sea water was then removed and

embryos were lysed in 50 μl of lysis mixture prepared by mixing 500 μL of DirectPCR Cell

Lysis Reagent (Viagen Biotech Inc., Los Angeles, CA, Cat # 301-C) with 1 μl of Proteinase

K (20 mg/ml, Life Technologies, Carlsbad, CA). The embryos were thoroughly mixed in

lysis mixture and incubated at 68°C for 15 minutes, followed by 95°C for 10 minutes.

PCR amplification of targeted sequences

Targeted sequences were individually PCR-amplified directly from lysate from embryos

targeted with the respective sgRNA, and from “negative control” lysate (from embryos

electroporated with Eef1a1>nls∷Cas9∷nls and U6>Negative Control sgRNA vector). Primers

(Supplementary Table 4) were designed to flank target sites as to obtain PCR products in the

size range of 108–290bp with an exception of the sequence targeted by Ebf.3 (“Ebf.774” in

Stolfi et al. 2014) and Ebf.4 sgRNAs, for which the designed primers resulted in a product

size of 350 bp. Potential off-target sites predicted for sgRNAs Ebf.3

(CTCGCAACGGGGACAACAGGGGG, genome position KhC8:2,068,844-2,068,866) and

Fgf4/6.1 (TATTTTAATTCTGTACCTGTGGG, genome position

KhC9:6,318,421-6,318,443) were amplified to test for off-target CRISPR/Cas9 activity with

the primers: 5′-CCAGCACTTCAGAGCAATCA-3′ and 5′-

TGACGTCACACTCACCGTTT-3′ (Ebf.3), and 5′-AACGATTGTCCATACGAGGA-3′ and 5′-ACTTCCCAACAGCAAACTGG-3′ (Fgf/6.1).

For each targeted sequence, 12.5 μL PCR reactions were set up with final concentrations of

600 nM each primer, 300 μM dNTPs, 1 mM MgSO4, 2X buffer, and 0.05 U/μl Platinum Pfx

DNA polymerase (Life Technologies), and subjected to the following PCR program: an

initial cycle of 10 minutes at 95°C, followed by 30 cycles of 30 seconds at 94°C, 30s at 60°C

and 30s at 68°C, and a final cycle of 3 minutes at 68°C. PCR reactions were quickly checked

on an agarose gel for the presence/absence of amplicon. Those that resulted in a single band

were not initially purified. For those reactions with more than one band, the correct

amplicon (selected based on expected size) was gel purified using a Nucleospin Gel Clean-

up Kit (Macherey-Nagel, Duren, Germany). Purified and unpurified PCR products were then

pooled for subsequent processing. The majority of PCR products amplified from larvae

treated with Cas9 + gene-targeting sgRNA were pooled in Pool 1. All products from larvae

treated with Cas9 + “negative control” sgRNA were pooled in Pool 2. For those sequences

targeted by distinct sgRNAs but amplified using the same set of flanking primers, their PCR

products were split into separate pools, as to allow for separate efficacy estimates.

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Sequencing library preparation

The PCR product pools were electrophoresed on ethidium bromide-stained, 1% agarose gel

in 0.5X Tris-Acetate-EDTA (TAE) buffer and a band of ~150–300 bp was excised

(Nucleospin gel and PCR cleanup kit, Macherey-Nagel). 102–235 ng of each pool was used

as a starting material to prepare sequencing libraries (protocol adapted from http://

wasp.einstein.yu.edu/index.php/Protocol:directional_WholeTranscript_seq). Ends were

repaired using T4 DNA polymerase (New England Biolabs, Ipswich, MA) and T4

Polynucleotide Kinase (New England Biolabs), and then A-tailed using Klenow fragment

(3′→5′ exo-) (New England Biolabs) and dATP (Sigma-Aldrich, St. Louis, MO). Each

pool was then ligated to distinct barcoded adapters. (NEXTflex DNA Barcodes - BioO

Scientific Cat# 514101). The six barcodes used in this study were: CGATGT, TGACCA,

ACAGTG, GCCAAT, CAGATC and CTTGTA. At this step, the adapter-ligated DNA

fragments were purified twice using Ampure XP beads (Beckman Coulter, Brea, CA). The

final amplification, using primers included with NEXTflex adapters, was done using the

PCR program: 2 minutes at 98°C followed by 8 cycles of 30 seconds at 98°C; 30 seconds at

60°C; 15 seconds of 72°C, followed by 10 minutes at 72°C. Ampure XP bead-based

selection was performed twice, and the libraries were quantified using qPCR. The libraries

were then mixed in equimolar ratio to get a final DNA sequencing library concentration of 4

nM. The multiplexed library was sequenced by Illumina MiSeq V2 platform (Illumina, San

Diego, CA) using 2×250 paired end configuration.

Next generation sequencing data analysis

FastQ files obtained from sequencing were de-multiplexed and subjected to quality control

analysis. FastQ reads were mapped to the 2008 KyotoHoya genome assembly (Satou et al. 2008) by local alignment using Bowtie2.2 (Langmead and Salzberg 2012). Single end reads

were also mapped to a reduced genome assembly consisting of only those scaffolds

containing the targeted genes. This allowed for a much faster and accurate alignment using

Bowtie2.2. The SAM file generated was converted into a BAM file using samtools (Li et al. 2009). The BAM file was sorted and indexed to visualize reads on Integrative Genomics

Viewer (IGV) (Robinson et al. 2011). Most mutagenesis rates were obtained by counting

indels in IGV. For some targets with partially overlapping aplicon sequences, custom Python

scripts were written to parse the BAM file to get estimated rate of mutagenesis. Since a

successful CRISPR/Cas9-mediated deletion or insertion should eliminate or disrupt all or

part of the protospacer + PAM sequence (jointly termed the “pineapple”), we simply looked

for mapped reads in which the pineapple was not fully present. When appropriate, the rate of

naturally occurring indels around each target, as detected in reads from “negative control”

embryos, was subtracted from the raw efficacy rates. Custom python scripts used are

available upon request. Matplotlib (http://matplotlib.org) was used for plotting, Numpy

(http://numpy.org) and Pandas (http://pandas.pydata.org) were used for data mining. All

predictive algorithm scores were generated using CRISPOR (http://crispor.tefor.net/)

(HAEUSSLER et al. 2016).

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http://wasp.einstein.yu.edu/index.php/Protocol:directional_WholeTranscript_seq

http://wasp.einstein.yu.edu/index.php/Protocol:directional_WholeTranscript_seq

http://matplotlib.org

http://numpy.org

http://pandas.pydata.org


Nucleotide Enrichment Analysis

We used log-odds score as a measure to estimate how enriched each nucleotide was at a

given position in the 43bp region of interest (excluding position 1 of the protospacer, and the

‘GG’ of the PAM). Log-odds score was defined as the base-2 logarithm of the ratio of

probability of observing nucleotide ‘N’ at position ‘x,’ and the background probability of

observing nucleotide ‘N’ by random chance, given its frequency in our sample space (all

sgRNA targets, n=83). A positive or negative log-odds score reflects enrichment or

depletion, respectively, of each nucleotide at a given position.

Mathematically,

px = probability of finding nucleotide ‘N’ at position ‘x’

pb = background probability of finding nucleotide ‘N’ at position ‘x’ by chance

Receiver Operating Characteristic (ROC) curve

For a binary classifier (“good” vs. “bad” sgRNA), there are four possible outcomes: True

Positive (TP), False Positive (FP), True Negative (TN), and False Negative (FN). If the

predicted classification of the sgRNA by our model was “good” or “bad”, and it was

supported by our experimental data (i.e. the empirical mutagenesis rate was above or below

24.5% respectively), it was marked as a “True Positive” or a “True Negative,” respectively.

If the experimental data failed to support it, it was marked as a “False Positive” or a “False

Negative,” respectively. The true positive rate (TPR), or “Sensitivity”, was defined as the

proportion of empirically good sgRNAs that were correctly predicted as good [TPR =

TP/(TP + FN)]. Similarly, the true negative rate (TNR), or “Specificity”, was defined as the

proportion of empirically bad gRNAs that were correctly predicted as bad [TNR = TN/(TN

+ FP)]. The false positive rate (FPR) is 1 - Specificity. In figure 3c, we plotted the true

positive rates against the false positive rates, all obtained by applying different Fusi/Doench

score thresholds (ranging from 0 to 100) to the predictions generated by our model (see

Supplementary Table 2).

Combinatorial sgRNA electroporation to induce large deletions

Embryos were electroporated with 25 μg Eef1a1>nls∷Cas9∷nls and two vectors from the set

of validated sgRNA plasmids for each targeted gene (50 μg per sgRNA vector). Embryos

were grown for 12 hpf at 18°C, pooled, and genomic DNA extracted from them using

QIAamp DNA mini kit (Qiagen). Deletion bands were amplified in PCR reactions using Pfx

platinum enzyme as described above (see “PCR amplification of targeted sequences”) and

a program in which the extension time was minimized to 15 seconds only, in order to

suppress the longer wild-type amplicon and promote the replication of the smaller deletion

band. Primers used were immediately flanking the sequences targeted by each pair of

sgRNAs (Supplementary Table 4). Products were purified from agarose gels, A-overhung

and TOPO-cloned. Colonies were picked, cultured, prepped and sequence.

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Synthesis and electroporation of unpurified sgRNA PCR expression cassettes

U6>Eb/.3 and U6>Negative Control sgRNA expression cassettes were amplified from their

respective plasmids using the primers U6 forward (5′-TGGCGGGTGTATTAAACCAC-3′)

and sgRNA reverse (5′-GGATTTCCTTACGCGAAATACG-3′) in reactions of final

concentrations of 600 nM each primer, 300 μM dNTPs, 1 mM MgSO4, 2X buffer, and 0.05

U/μl Platinum Pfx DNA polymerase (Life Technologies), and subjected to the following

PCR program: an initial cycle of 3 minutes at 95°C, followed by 30 cycles of 30 seconds at

94°C, 30s at 55°C and 2 minutes at 68°C, and a final cycle of 5 minutes at 68°C.

U6>sgRNA(F+E)∷eGFP (STOLFI et al. 2014) was amplified as above but using Seq

forward primer (5′-AGGGTTATTGTCTCATGAGCG-3′) instead. For phenotyping Ebf-

dependent expression of Islet reporter in MN2 motor neurons (STOLFI et al. 2014),

embryos were co-electroporated with 35–40 μg of Sox1/2/3> nls∷Cas9∷nls, 5–15 μg of

Sox1/2/3>H2B∷mCherry/eGFP, 30–40 μg of Isl>eGFP/mCherry, and either 25 μg of

U6>Ebf.3 plasmid or 25 μl (~2.5 ug) of unpurified PCR product.

sgRNA expression cassette assembly by One-step Overlap PCR (OSO-PCR)

sgRNA PCR cassettes were constructed using an adapted One-step Overlap PCR (OSO-

PCR) protocol (Urban et al. 1997). Basically, a desired protospacer sequence is appended 5′ to a forward primer (5′-GTTTAAGAGCTATGCTGGAAACAG-3′) and its reverse

complement is appended 5′ to a reverse primer (5′-ATCTATACCATCGGATGCCTTC-3′).

These primers are then added to a PCR reaction at limiting amounts, together with u6

forward (5′-TGGCGGGTGTATTAAACCAC-3′) and sgRNA reverse (5′-

GGATTTCCTTACGCGAAATACG-3′) primers and separate template plasmids containing

the U6 promoter (U6>XX) and the sgRNA scaffold (XX>sgRNA F+E). Plasmids are

available from Addgene (https://www.addgene.org/Lionel_Christiaen/). The

complementarity between the 5′ ends of the inner primers bridges initially separate U6 and

sgRNA scaffold sequences into a single amplicon, and because they are quickly depleted,

the entire cassette is preferentially amplified in later cycles by the outer primers (see Figure

5 and Supplementary Protocol for details). Final, unpurified reactions should contain PCR

amplicon at ~100 ng/μl, as measured by image analysis after gel electrophoresis

(Supplementary Figure 5).

Measuring mutagenesis efficacies of sgRNAs by Sanger sequencing

OSO-PCR cassettes were designed and constructed for the expression of 7 sgRNA targeting

exons 10–12 that code for part of the IPT and HLH domains of Ebf (Figure 6a,

Supplementary Table 3). Embryos were electroporated with 25 μl of unpurified OSO-PCR

product and 25 μg Eef1a1>nls∷Cas9∷nls, and grown to hatching. For the replication

experiment (Supplementary Table 6) 75 μg of sgRNA vectors (Gata4/5/6.2, Gata4/5/6.3,

Gata4/5/6.4, Neurog.1, Neurog.2) were each co-electroporated with 25 μg

Eef1a1>nls∷Cas9∷nls. This was repeated over two separate batches of embryos.

All larvae were allowed to hatch and genomic DNA was extracted using the QiaAmp DNA

mini kit (Qiagen). The Ebf target region was PCR-amplified using the following primers:

(Forward primer: 5′-CTCCACATGCCTCAACTTTG-3′, Reverse primer: 5′-

TGTTCCGCCAAATTGTGAAG-3′). For Gata4/5/6 target sequences, the primers used were

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the corresponding ones from the NGS experiment, while a novel pair of primers was used to

amplify the Neurog locus (Forward primer: 5′-AAGTACGGAGAGCAGAATACC-3′,

Reverse primer: 5′-CTTCTAGTGCGTCATTAAGACC-3′). PCR was performed in 35

cycles using Platinum Pfx DNA polymerase. The resulting PCR products were gel- or

column-purified, and sequenced using either a flanking PCR primer or an internal

sequencing primer (Ebf internal: 5′-AATTGGCTGACAGGTTGGAG-3′, Neurog internal:

5′-GCTCTTGCTACAAAATGTTGG-3′).

The resulting.ab1 sequencing files were then analyzed by ab1 Peak Reporter webtool (ROY

and SCHREIBER 2014) (https://apps.thermofisher.com/ab1peakreporter/)(Supplementary

Table 5). To quantify the peak “shifts” resulting from CRISPR/Cas9-induced short indels

(Supplementary Figure 6), we calculated the sum of “maximum signal 7 scan filtered ratio”

(MaxSig7Scan Sum) values of minor peaks at each position in a 30 bp window starting from

the third bp in the target sequence from the PAM (the most likely Cas9 cut site). The mean

MaxSig7Scan Sum was calculated across all 30 bp of this window, resulting in a “raw

peakshift score”. The same was repeated for the 30 bp window immediately 5′ to the cut

site in the sequencing read, for a peakshift “baseline” estimate. This baseline was subtracted

from the raw peakshift score to give the “corrected peakshift score”, a relative quantification

of indel frequency, and therefore of the mutagenesis efficacy of the sgRNA used.

Whole-exome sgRNA predictions in Ciona

We used all transcribed regions in the ENSEMBL 65 transcript models (AKEN et al. 2016),

extended them by 200 bp on each side, searched for all possible NGG-20bp sgRNA targets

in these sequences and ran them through the command-line version of CRISPOR

(HAEUSSLER et al. 2016) which aligns 20mers using BWA (LI AND DURBIN 2009) in

iterative mode, ranks off-targets by CFD or MIT scores and calculates the Fusi/Doench 2016

efficiency scores (Fusi et al. 2015; Doench et al. 2016). Efficiency scores were also

translated to percentiles for better ease of use, e.g. a raw Fusi/Doench score of 60 translates

to the 80th percentile, meaning that 80% of scored guides are lower than 60. All results are

then written to a UCSC BigBed file (Raney et al. 2014) for interactive visualization. The

BigBed file can be loaded into all popular genome browsers, like Ensembl (Yates et al. 2016), IGV (Robinson et al. 2011) or GBrowse (Stein et al. 2002). The track is available on

the ci2 assembly on the UCSC Genome Browser (http://genome.ucsc.edu), in the track

group “Genes and Gene Predictions”. The source code is available as part of the UCSC

Genome Browser source tree at: https://github.com/ucscGenomeBrowser/kent/tree/

master/src/hg/makeDb/crisprTrack

Embryo imaging

Fluorescent in situ hybridization of eGFP or Foxf coupled to immunohistochemsitry was

carried out as previously described (Beh et al. 2007; Stolfi et al. 2014). Images were taken

on a Leica Microsystems inverted TCS SP8 X confocal microscope or a Leica DM2500

epifluorescence microscope. Mouse monoclonal anti-β-Gal Z3781 (Promega, Madison, WI)

was used diluted at 1:500. Goat anti-Mouse IgG (H+L) Secondary Antibody Alexa Fluor

568 conjugate (Life Technologies) was used diluted at 1:500.

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https://apps.thermofisher.com/ab1peakreporter/

http://genome.ucsc.edu

https://github.com/ucscGenomeBrowser/kent/tree/master/src/hg/makeDb/crisprTrack

https://github.com/ucscGenomeBrowser/kent/tree/master/src/hg/makeDb/crisprTrack

Supplementary Material

Refer to Web version on PubMed Central for supplementary material.

Acknowledgments

We are grateful to Farhana Salek, Kristyn Millan, and Aakarsha Pandey for technical assistance; Tara Rock for advice on next-generation sequencing; Rahul Satija for sequencing the libraries and for his invaluable insights into the sgRNA sequence analysis; Justin S. Bois, Shyam Saladi, Elena K. Perry, and the High Performance Computing team at NYU for their help troubleshooting the bioinformatic analysis. This work was funded by an NIH K99 HD084814 award to A.S., NIH R01 GM096032 award to L.C., and an NYU Biology Masters Research Grant to S.G.

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Highlights

• Activity of 83 sgRNAs targeting 23 genes in Ciona embryos was analyzed by

next-generation sequencing

• A new method of sgRNA expression vector construction by One-Step Overlap

PCR (OSO-PCR) was developed

• sgRNAs can be transcribed in vivo from electroporated unpurified PCR

products

• A high correlation was found between varying activity of several Ebf sgRNAs

and frequency of Ebf loss-of-function phenotype in F0

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Figure 1. Next-Generation Sequencing approach to validating sgRNAs for use in Ciona embryosa) Schematic for next-generation sequencing approach to measuring mutagenesis efficacies

of sgRNAs expressed in F0 Ciona embryos. See results and materials and methods for

details. b) Representative view in IGV browser of coverage (grey areas) of sequencing reads

aligned to the reference genome. “Dip” in coverage of reads from embryos co-electroporated

with Eef1a1>Cas9 and U6>Htr7-r. 1 sgRNA vector indicates CRISPR/Cas9-induced indels

around the sgRNA target site, in the 2nd exon of the Htr7-related (Htr7-r) gene. Colored bars

in coverage indicate single-nucleotide polymorphisms/mismatches relative to reference

genome. c) Diagram representing a stack of reads bearing indels of various types and sizes,

aligned to exact target sequence of Htr7-r. 1 sgRNA. d) Plot of mutagenesis efficacy rates

measured for all sgRNAs, ordered from lowest (0%) to highest (59.63%). Each bar

represents a single sgRNA. e) Box-and-whisker plots showing the size distribution of

insertions and deletions caused by Ebf.3 or Lef1.2 sgRNAs.

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Figure 2. Correlations between sgRNA sequence composition and mutagenesis efficacya) WebLogos representing the nucleotide composition at each variable position of the

protospacer (nt 2–20, X axis), in top 25% and bottom 25% performing sgRNAs. b) Log-

odds scores depicting the frequency of occurrence for nucleotides in the top 25% and bottom

25% sgRNAs, at all positions of the protospacer, PAM, and flanking regions. Position “1” of

the protospacer has been omitted from the analysis, due to this always being “G” for PolIII-

dependent transcription of U6-promoter-based vectors. Likewise, the “GG” of the PAM has

also been omitted, as this sequence is invariant in all targeted sites. Positive and negative

log-odds scores reflect abundance and depletion, respectively, of a specific nucleotide at a

given position relative to its random occurrence in our sample space. See materials and methods for details.

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Figure 3. Using Fusi/Doench scores to predict mutagenesis efficacies of sgRNAs in Cionaa) Mutagenesis efficacy rate of each sgRNA plotted against the same sgRNA’s Fusi/Doench

algorithm score, obtained from CRISPOR. The Spearman’s rank correlation coefficient (rho)

is 0.435 (p = 3.884e-05). b) sgRNAs grouped by sorted Fusi/Doench predicted scores (left:

>60; right: <50). 18 of 23 sgRNAs of Fusi/Doench score over 60 showed a measured

mutagenesis efficacy (MUT%) over 24%, classified as “good” (shaded green). In contrast,

only 4 from the same set had a MUT% under 24%, classified as “bad”. “Good” and “bad”

classifications were based on phenotype frequency in F0 (see text for details). Out of 25

sgRNAs with Fusi/Doench score under 50, 17 were “bad”, while only 8 were “good”. c) A

Receiver Operating Characteristic (ROC) curve assesses the credibility of using Fusi/Doench

score cutoff (from 0 to 100) to classify sgRNAs as either “good” (>24.5% efficacy) or “bad”

(≤24.5% efficacy). Using Fusi/Doench cutoffs as such a classifier returns an AUC of 0.77

(black line), while an AUC of 0.5 (dashed red line) represents the performance of a classifier

solely based on random chance. The optimal Fusi/Doench cutoff (above which a score is

likely to indicate “good” sgRNAs) was found to be between 50 and 55. See materials and methods and Supplementary Table 2 for details.

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Figure 4. Combinatorial targeting of Foxf results in large deletionsa) Diagram of Foxf locus, showing positions targeted by Foxf.4 and Foxf.2 sgRNAs. Foxf.4 targets a non-coding, cis-regulatory sequence 881 base pairs (bp) upstream of the

transcription start site of Foxf. Foxf.2 targets a coding sequence in exon 1 of Foxf. The

distance between the target sites is 2132 bp, and encompasses most of exon 1, the core

promoter, and cis-regulatory modules that drive Foxf expression in the head epidermis and

trunk ventral cells (TVCs) (BEH et al. 2007). Blue arrows indicate primers used to amplify

the region between the target sites. In wild-type embryos, the resulting PCR product is ~2.4

kilobase pairs (kbp). b) Alignment of cloned PCR products amplified using the primers

indicated in (a), from wild-type (wt) embryos, and from embryos electroporated with 25 μg

Eef1a1>nls∷Cas9∷nls and 50 μg each of U6>Foxf.2 and U6>Foxf.4. Colonies 03, 04, and 06

shown containing large deletions between the approximate sites targeted by the two

sgRNAs, indicating non-homologous end-joining (NHEJ) repair from two separate double

stranded break events as a result of combinatorial action of Foxf.2 and Foxf.4 sgRNAs. c) In situ hybridization for Foxf (green) showing strong expression throughout the head epidermis

in embryos electroporated with 10 μg Fog>H2B∷mCherry (red), 50 μg Fog>nls∷Cas9∷nls and 45 μg of U6>Ebf.3. Foxf expression is essentially wild-type, as Ebf function is not

required for activation of Foxf in the epidermis. d) In situ hybridization for Foxf (green)

showing patchy expression in the head epidermis of embryos electroporated with 10 μg

Fog>H2B∷mCherry (red), 50 μg Fog>nls∷Cas9∷nls and 45 μg each of U6>Foxf.2 and

U6>Foxf.4. Loss of in situ signal in some transfected head epidermis cells indicates loss of

Foxf activation, presumably through deletion of all or part of the upstream cis-regulatory

sequences by CRISPR/Cas9. Scale bars = 25 μm.

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Figure 5. One-step Overlap Polymerase Chain Reaction (OSO-PCR) for the high-throughput construction of sgRNA expression cassette librariesa) Diagram of OSO-PCR for amplification of U6>sgRNA expression cassettes in which the

target-specific sequence of each (red) is encoded in complementary overhangs attached to

universal primers. 1:10 dilution of these primers ensures that the overlap product, the entire

U6>sgRNA cassette, is preferentially amplified (see methods for details). b) Agarose gel

electrophoresis showing products of four different U6>sgRNA OSO-PCRs. The desired

product is ~1.2 kilobase pairs (kbp) long. 2logL = NEB 2-Log DNA ladder. c) Detailed

diagram of how the overlap primers form a target-specific bridge that fuses universal U6

promoter and sgRNA scaffold sequences.

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Figure 6. Linear relationship between sgRNA efficacy and mutant phenotype frequency in F0a) Diagram of Ebf locus, showing exons coding for DNA-binding (DBD), IPT, and helix-

loop-helix (HLH) domains. Colored dots indicate exons targeted by the Ebf-targeting

sgRNAs used to validate the OSO-PCR method for genetic loss-of-function. b) Larvae co-

electroporated with Sox1/2/3>nls∷Cas9∷nls, Islet>eGFP, and 25 μl (~2.5 μg) unpurified

U6>NegativeControl PCR or c) 25 μl (~2.5 μg) unpurified U6>Ebf.3 PCR, or d) 25 μg

U6>Ebf.3 plasmid. Islet>eGFP reporter plasmid is normally expressed in MN2 motor

neurons (“Islet+ MN2”, green), which is dependent on Ebf function. Islet>eGFP was

expressed in MN2s in 75 of 100 negative control embryos. In embryos electroporated with

unpurified U6>Ebf.3 PCR products or U6>Ebf.3 plasmid, only 16 of 100 and 17 of 100

embryos, respectively, had Islet>eGFP expression in MN2s. This indicates similar loss of

Ebf function in vivo by either unpurified PCR or purified plasmid sgRNA delivery method.

c) Plot comparing mutagenesis efficacies of the OSO-PCR-generated sgRNAs indicated in

panel (a) (measured by Sanger sequencing, see text for details) and the ability to cause the

Ebf loss-of-function phenotype (loss of Islet>mCherry reporter expression in MN2s in

Sox1/2/3>H2B∷eGFP+ embryos). The nearly perfect inverse correlation between sgRNA

mutagenesis efficacy and Islet>mCherry expression indicates a linear relationship between

sgRNA activity and mutant phenotype frequency in electroporated embryos. Ebf.3 sgRNA

data point is bracketed, because its mutagenesis efficacy was not measured by Sanger

sequencing but comes from the NGS data collected in this study.

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Table 1Genes targeted for CRISPR/Cas9-mediated mutagenesis

The 23 genes targeted in the initial screen, each identified here by official gene symbol, aliases, and

KyotoHoya identifier.

# Gene Symbol Aliases 2012 KyotoHoya ID

1 Bmp2/4 Bone morphogenetic protein 2/4 KH.C4.125

2 Ddr Discoidin Domain Receptor Tyrosine Kinase 1/2 KH.C9.371

3 Ebf Collier/Olf/EBF; COE KH.L24.10

4 Eph.a Ephrin type-A receptor.a; Eph1 KH.C1.404

5 Ets.b Ets/Pointed2 KH.C11.10

6 Fgf4/6 Fibroblast growth factor 4/6; FGF, unassigned 1 KH.C1.697

7 Fgf8/17/18 Fibroblast growth factor 8/17/18 KH.C5.5

8 Fgfr Fibroblast growth factor receptor KH.S742.2

9 Foxf FoxF KH.C3.170

10 Foxg-r Foxg-related; Orphan Fox-4; Ci-ZF248 KH.C5.74

11 Fzd5/8 Frizzled5/8 KH.C9.260

12 Gata4/5/6 GATA-a KH.L20.1

13 Hand Heart And Neural Crest Derivatives Expressed 1/2 KH.C14.604

14 Hand-r Hand-related; Hand-like; NoTrlc KH.C1.1116

15 Htr7-r 5-Hydroxytryptamine Receptor 7-related KH.S555.1

16 Isl Islet1/2 KH.L152.2

17 Lef1 Lef/TCF KH.C6.71

18 Mrf Muscle regulatory factor; MyoD KH.C14.307

19 Neurog Neurogenin; Ngn KH.C6.129

20 Nk4 Nkx2-5; Tinman KH.C8.482

21 Rhod/f RhoD/F; Rif KH.C1.129

22 Tle.b Groucho2 KH.L96.50

23 Tll Tolloid-like; Tolloid KH.C12.156


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